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Non-invasive Device for the Screening and Diagnosis of Sleep Apnea Syndrome (Episas)

Primary Purpose

Obstructive Sleep Apnea

Status
Completed
Phase
Not Applicable
Locations
France
Study Type
Interventional
Intervention
3D acquisition of maxillofacial characteristics
Sponsored by
University Hospital, Grenoble
About
Eligibility
Locations
Arms
Outcomes
Full info

About this trial

This is an interventional diagnostic trial for Obstructive Sleep Apnea focused on measuring Sleep apnea diagnosis, 3D acquisition

Eligibility Criteria

40 Years - 75 Years (Adult, Older Adult)MaleAccepts Healthy Volunteers

Inclusion Criteria:

  • BMI < 35 kg/m²
  • caucasian men
  • patients from the sleep laboratory (CHU Grenoble Alpes) admitted for a polysomnography
  • Patient who has given free and informed consent in writing

Exclusion Criteria:

  • history of maxillofacial surgery
  • dental malocclusion
  • patient involved in another clinical research study
  • patient not affiliated with social security
  • patient deprived of liberty or hospitalized without consent

Sites / Locations

  • Grenoble Alpes University Hospital

Arms of the Study

Arm 1

Arm Type

Other

Arm Label

OSA diagnosis with 3D acquisition

Arm Description

OSA diagnosis with 3D acquisition

Outcomes

Primary Outcome Measures

Establish and evaluate a predictive model for OSA diagnosis by 3D acquisition of characteristics maxillofacial
apnea hypopnea index will be measured by polysomnography for each patient and compared to a predictive model establish from body mass index and 3D acquisition (cricomental distance...)

Secondary Outcome Measures

Sensitivity study from different stages of OSA severity
OSA severity stages will be apnea hypopnea index <5, <10, <15
Compare diagnosis performances of predictive model and Berlin or NoSAS questionnaires
Correlation between the Berlin or NoSAS score and the predictive model results
Evaluate performances of the combination (Berlin questionnaire + predictive model) to estimate the OSA risk
Calculate the sensitivity, specificity, predictive positive value and predictive negative value of the combination

Full Information

First Posted
August 13, 2018
Last Updated
February 9, 2021
Sponsor
University Hospital, Grenoble
Collaborators
SATT Linksium GRENOBLE, ARTEHIS, ARCTIC
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1. Study Identification

Unique Protocol Identification Number
NCT03632382
Brief Title
Non-invasive Device for the Screening and Diagnosis of Sleep Apnea Syndrome
Acronym
Episas
Official Title
Non-invasive Device for the Screening and Diagnosis of Sleep Apnea Syndrome
Study Type
Interventional

2. Study Status

Record Verification Date
February 2021
Overall Recruitment Status
Completed
Study Start Date
July 27, 2018 (Actual)
Primary Completion Date
July 27, 2018 (Actual)
Study Completion Date
September 8, 2020 (Actual)

3. Sponsor/Collaborators

Responsible Party, by Official Title
Sponsor
Name of the Sponsor
University Hospital, Grenoble
Collaborators
SATT Linksium GRENOBLE, ARTEHIS, ARCTIC

4. Oversight

Studies a U.S. FDA-regulated Drug Product
No
Studies a U.S. FDA-regulated Device Product
No
Data Monitoring Committee
No

5. Study Description

Brief Summary
This prospective study aims to establish and evaluate a predictive model to diagnose OSA with maxillofacial characteristics 3D acquisition.
Detailed Description
Polysomnography is the gold-standard for obstructive sleep apnea (OSA) diagnosis. However, OSA is still undiagnosed. Maxillofacial profile can influence OSA severity. Morphological characteristics can be identified but are not enough measurable and analysable by physicians. 3D acquisition of maxillofacial characteristics with a user-friendly tool, quick and low-priced could be used to obtain a predictive model as an OSA risk indicator. Thus, the aim of this study is to establish and evaluate a predictive model to diagnose OSA with maxillofacial characteristics 3D acquisition.

6. Conditions and Keywords

Primary Disease or Condition Being Studied in the Trial, or the Focus of the Study
Obstructive Sleep Apnea
Keywords
Sleep apnea diagnosis, 3D acquisition

7. Study Design

Primary Purpose
Diagnostic
Study Phase
Not Applicable
Interventional Study Model
Single Group Assignment
Model Description
Prospective
Masking
None (Open Label)
Allocation
N/A
Enrollment
280 (Actual)

8. Arms, Groups, and Interventions

Arm Title
OSA diagnosis with 3D acquisition
Arm Type
Other
Arm Description
OSA diagnosis with 3D acquisition
Intervention Type
Diagnostic Test
Intervention Name(s)
3D acquisition of maxillofacial characteristics
Intervention Description
A 3D acquisition of maxillofacial characteristics will be performed for each patient in order to validate a predictive model comparable to data obtained by polysomnography
Primary Outcome Measure Information:
Title
Establish and evaluate a predictive model for OSA diagnosis by 3D acquisition of characteristics maxillofacial
Description
apnea hypopnea index will be measured by polysomnography for each patient and compared to a predictive model establish from body mass index and 3D acquisition (cricomental distance...)
Time Frame
1 measure at inclusion
Secondary Outcome Measure Information:
Title
Sensitivity study from different stages of OSA severity
Description
OSA severity stages will be apnea hypopnea index <5, <10, <15
Time Frame
1 measure at inclusion
Title
Compare diagnosis performances of predictive model and Berlin or NoSAS questionnaires
Description
Correlation between the Berlin or NoSAS score and the predictive model results
Time Frame
1 measure at inclusion
Title
Evaluate performances of the combination (Berlin questionnaire + predictive model) to estimate the OSA risk
Description
Calculate the sensitivity, specificity, predictive positive value and predictive negative value of the combination
Time Frame
1 measure at inclusion

10. Eligibility

Sex
Male
Minimum Age & Unit of Time
40 Years
Maximum Age & Unit of Time
75 Years
Accepts Healthy Volunteers
Accepts Healthy Volunteers
Eligibility Criteria
Inclusion Criteria: BMI < 35 kg/m² caucasian men patients from the sleep laboratory (CHU Grenoble Alpes) admitted for a polysomnography Patient who has given free and informed consent in writing Exclusion Criteria: history of maxillofacial surgery dental malocclusion patient involved in another clinical research study patient not affiliated with social security patient deprived of liberty or hospitalized without consent
Overall Study Officials:
First Name & Middle Initial & Last Name & Degree
Jean-Louis PEPIN
Organizational Affiliation
CHU Grenoble Alpes
Official's Role
Principal Investigator
Facility Information:
Facility Name
Grenoble Alpes University Hospital
City
Grenoble
Country
France

12. IPD Sharing Statement

Plan to Share IPD
No
Citations:
PubMed Identifier
35567881
Citation
Monna F, Ben Messaoud R, Navarro N, Baillieul S, Sanchez L, Loiodice C, Tamisier R, Joyeux-Faure M, Pepin JL. Machine learning and geometric morphometrics to predict obstructive sleep apnea from 3D craniofacial scans. Sleep Med. 2022 Jul;95:76-83. doi: 10.1016/j.sleep.2022.04.019. Epub 2022 Apr 29.
Results Reference
derived

Learn more about this trial

Non-invasive Device for the Screening and Diagnosis of Sleep Apnea Syndrome

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